Anbang Yao
Computer Vision and Pattern Recognition · 2016–2022
A researcher in the Science corpus: 8 papers; trusts 1,298 researchers and is trusted by 293 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 246 citations into it; #2,370 of 21,575 by trust here, #1,795 by citations
- Artificial Intelligence — 151 citations into it; #3,024 of 35,345 by trust here, #3,638 by citations
- Efficiency & Compression — 62 citations into it; #115 of 1,264 by trust here, #326 by citations
- Model Architectures — 54 citations into it
- Aerospace Engineering — 24 citations into it
- Optimization & Training — 16 citations into it
- Media Technology — 12 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
Whom Anbang Yao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Ross B. Girshick
- Geoffrey E. Hinton
- Karen Simonyan
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Christian Szegedy
- David G. Lowe
Who trusts Anbang Yao overall
- Aojun Zhou
- Yang He
- Frederick Tung
- Karim Ahmed
- Arun Mallya
- Shifeng Zhang
- Tao Kong
- Georgios Georgiadis
- Xiongwei Wu
- Wujie Wen
Papers from Anbang Yao's perspective
Ordered by how strongly the researchers Anbang Yao trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights (2017) — 1,135 citations
- Dynamic Network Surgery for Efficient DNNs (2016) — 1,158 citations
- HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection (2016) — 853 citations
- RON: Reverse Connection with Objectness Prior Networks for Object Detection (2017) — 419 citations
- Explicit Loss-Error-Aware Quantization for Low-Bit Deep Neural Networks (2018) — 93 citations
- Learning Two-View Correspondences and Geometry Using Order-Aware Network (2019) — 368 citations
- Omni-Dimensional Dynamic Convolution (2022) — 447 citations
- Knowledge Transfer via Dense Cross-Layer Mutual-Distillation (2020) — 70 citations